code: def test_actual_results_numerosity_reduction():
      """Test that the actual results are the expected ones."""
      bossvs = BOSSVS(
          word_size=4,
          n_bins=3,
          window_size=0.5,
          window_step=0.5,
          anova=False,
          drop_sum=False,
          norm_mean=False,
          norm_std=False,
          strategy="quantile",
          alphabet=None,
          numerosity_reduction=True,
          use_idf=False,
          smooth_idf=False,
          sublinear_tf=True,
      )
  
      X_windowed = X.reshape(8, 2, 10).reshape(16, 10)
      sfa = SymbolicFourierApproximation(
          n_coefs=4,
          drop_sum=False,
          anova=False,
          norm_mean=False,
          norm_std=False,
          n_bins=3,
          strategy="quantile",
          alphabet=None,
      )
      y_repeated = np.repeat(y, 2)
      X_sfa = sfa.fit_transform(X_windowed, y_repeated)
      X_word = np.asarray(["".join(X_sfa[i]) for i in range(16)])
      X_word = X_word.reshape(8, 2)
      not_equal = np.c_[
          X_word[:, 1:] != X_word[:, :-1], np.full(8, True)
      ]
      X_bow = np.asarray(
          [" ".join(X_word[i, not_equal[i]]) for i in range(8)]
      )
      X_class = np.array([" ".join(X_bow[y == i]) for i in range(2)])
  
      tfidf = TfidfVectorizer(
          norm=None, use_idf=False, smooth_idf=False, sublinear_tf=True
      )
      tfidf_desired = tfidf.fit_transform(X_class).toarray()
      vocabulary_desired = {
          value: key for key, value in tfidf.vocabulary_.items()
      }
  
      # Tf-idf
      tfidf_actual = bossvs.fit(X, y).tfidf_
  
      # Decision function
      decision_function_actual = bossvs.decision_function(X)
      decision_function_desired = cosine_similarity(
          tfidf.transform(X_bow), tfidf_desired
      )
  
      # Predictions
      y_pred_actual = bossvs.predict(X)
      y_pred_desired = decision_function_desired.argmax(axis=1)
  
      # Testing
      assert bossvs.vocabulary_ == vocabulary_desired
      np.testing.assert_allclose(
          tfidf_actual, tfidf_desired, atol=1e-5, rtol=0
      )
      np.testing.assert_allclose(
          decision_function_actual,
          decision_function_desired,
          atol=1e-5,
          rtol=0,
      )
      np.testing.assert_allclose(
          y_pred_actual, y_pred_desired, atol=1e-5, rtol=0
      )
  
file_path: pyts/pyts/classification/tests/test_bossvs.py
imports: import numpy
  import pytest
  import re
  from sklearn.metrics.pairwise import cosine_similarity
  from sklearn.feature_extraction.text import TfidfVectorizer
  from pyts.classification import BOSSVS
  from pyts.approximation import SymbolicFourierApproximation
label_desc: Use image node_id 3 for calling a global function with example usage: test_actual_results_numerosity_reduction() without return types